DESCRIPTION :
Research on mobile systems focuses on collecting and analyzing spatiotemporal datasets, providing valuable insights into the mobility patterns of users and goods. However, gathering such data presents significant challenges, particularly in developing non-intrusive data acquisition strategies. These strategies must also consider the energy constraints of tracking devices, ensuring prolonged operation without compromising data quality or user experience.
Bluetooth Low Energy (BLE) emerges as a promising candidate technology for non-intrusive and energy-efficient data collection in mobile systems. BLE tag systems provide a cost-effective solution for localizing assets, including people and high-value goods. These systems determine presence by capturing BLE signals via a receiver that knows its own position, typically providing binary information, indicating whether an object is present or not in the vicinity. In this project, we aim to go beyond binary data by analyzing and interpreting signal measurements to reconstruct the mobility patterns of tagged objects. A key advantage of conducting a global analysis is the ability to correlate diverse events, such as tag detections and transport movements between facilities, allowing us to infer common behaviors and gain deeper insights into mobility patterns.
This project is a collaboration between Inria and La Poste, combining academic research expertise with real-world operational challenges. The partnership provides access to large-scale deployment environments and actual logistics warehouses, facilitating the development and validation of explored solutions.
The mission is to set up an experimental platform to automate and manage all processes involved in the project, including:
* The capture and processing of BLE signals from tags in lab and real deployment scenarios,
* The interpretation of signal presence and absence over time and space to infer proximity events,
* And the integration of contextual data, such as known movement patterns or facility layouts, to refine contact detection and reduce false positives.
The mission is to establish an experimental platform for automating and managing all processes involved in the Mitik project. The main goal is to integrate all the stages that comprise the project's architecture more efficiently, with minimal error-prone processes, and automate time-consuming tasks. It includes infrastructure preparation, unifying code sources, ensuring compatibility between tools, and managing data, among others.
* Design, develop and deploy an experimental platform to integrate layers of Mitik project.
* Develop the tools necessary to plan, initiate, and manage experiments for implementing passive sniffers.
* Documentation writing
* Test and modify until validation.
Niveau de formation : Bac+5
Temps partiel / Temps plein : Plein temps
Type de contrat : Contrat à durée déterminée (CDD)
Compétences : Intelligence Artificielle, Bash Shell, Bluetooth Low Energy (Bluetooth), C ++ (Langage de Programmation), Débogage, Linux, GPS, Python (Langage de Programmation), Réseaux sans Fil, Scripting, Wireless Devices, Programming Languages, Anglais, Français, Sens de la Communication, Réseautage, Capacité de Persuasion, Enthousiasme, Esprit d'Équipe, Implication et Investissement, Innovation, UX (Expérience Utilisateur), Recherche, Algorithmes, Architecture, Systèmes Automatisés, Partenariats, Collecte de Données, Qualité des Données, Expérimentation, Dynamique de Groupe, Gestion des Infrastructures, Gestion de Projet
Courriel :
webmaster@inria.fr
Téléphone :
0139635511
Type d'annonceur : Employeur direct
